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Upendra Shardanand

dblp:54/3775 · DBLP profile ↗
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1ranked-venue papers
1as first author
0since 2021 · last 1995
—ORCID · none

Domains — the database's venue-derived domains; a paper can count in several

Human-computer interaction and ubiquitous computing · 1 · 1 first-author

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Databases, data mining, and information retrieval
1 paper
Recommender systems · 100%

Topics — the 4 heaviest of 4, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Recommender systems
collaborative filtering		 0.011995
Social Information Filtering: Algorithms for Automating "Word of Mouth" · CHI 1995
Recommender systems › social recommendation
social filtering		 0.011995
Social Information Filtering: Algorithms for Automating "Word of Mouth" · CHI 1995
Recommender systems
user similarity		 0.011995
Social Information Filtering: Algorithms for Automating "Word of Mouth" · CHI 1995
Recommender systems
music recommendation		 0.011995
Social Information Filtering: Algorithms for Automating "Word of Mouth" · CHI 1995

Methods — techniques the papers use, named apart from their topics

user study · 0.0collaborative filtering algorithms · 0.0
YearPublicationVenuePosition
1995 Social Information Filtering: Algorithms for Automating "Word of Mouth"
abstract
This paper describes a technique for making personalized recommendations from any type of database to a user based on similarities between the interest profile of that user and those of other users.In particular, we discuss the implementation of a networked system called Ringo, which makes personalized recommendations for music albums and artists.Ringo's database of users and artists grows dynamically as more people use the system and enter more information.Four different algorithms for making recommendations by using social information filtering were tested and compared.We present quantitative and qualitative results obtained from the use of Ringo by more than 2000 people.
Upendra Shardanand, Pattie Maes
 CHI1